As a method of increasing data transmission efficiency in a wireless communication system, there is MIMO technology.
An MIMO scheme is categorized into a single-user MIMO (SU-MIMO) scheme and a multi-user MIMO (MU-MIMO) scheme depending on whether pieces of data are capable of being simultaneously transmitted by using the same band when transmitting the pieces of data to a number of users.
It is known that the MU-MIMO scheme of simultaneously transmitting different data to a number of users by using the same band obtains higher frequency efficiency than that of the SU-MIMO scheme based on a multi-user diversity gain and a space multiplexing gain.
A performance of wireless communication is largely enhanced through beamforming of the MU-MIMO scheme. The beamforming concentrates transmission energy on one user or a specific user group, thereby increasing a signal-to-noise ratio (SNR) or a transmission speed.
The MU-MIMO scheme enhances performance by using an appropriate user scheduling technique of an access point (AP) or a base station (BS). For example, a diversity gain is obtained by simultaneously providing a service to users which have a good channel condition, or a multiplexing gain is obtained by simultaneously providing a service to users which use an orthogonal channel.
However, an issue of determining a user set capable of optimizing a gain is relevant to an issue of optimally allocating a beamforming matrix and transmission power, and thus, it is unable to easily make a conclusion.
Generally, in a case of using a beamforming strategy such as zero-forcing beamforming (ZFBF), a beamforming matrix is easily calculated, but brute-force search is still needed for user scheduling. For this reason, researchers propose a greedy algorithm which ensures sub-optimality and is low in complexity.
However, it is assumed that most of user scheduling algorithms already and accurately know all or most CSI before executing an algorithm.
In reality, it is impossible to obtain CSI from all users before transmission in an actual system. To this end, the amount of CSI is reduced by using a compression technique, but a process of transmitting a feedback acts as an overhead in a media access control (MAC) layer.
Moreover, the excessive compression of CSI largely restricts a performance of user scheduling.